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In all the four wavelet transforms, SVD postclassifier is the best suited one to achieve the high classification rate.
The aim is to obtain high classification rate, performance index, quality value with low false alarm, and missed classification.
Simulations demonstrate that the proposed method can provide sufficiently high classification rate in comparison with other fuzzy classification models.
Computer simulation results by them have demonstrated that the classification model provides a sufficiently high classification rate in comparison with that of other models proposed in the literature.
We proposed a dynamic encryption method via biometric information among frequency spectrums of ECG signals, which can guarantee both high classification rate (>90 %) and system energy efficiency.
We especially designed a dynamic keying method for signal encryption through biometric information among ECG signals, which can guarantee both high classification rate (>90%%) and energy efficiency.
Similar(40)
High classification rates demonstrate the superiority of the proposed system.
Likewise, MFCC-based features were used to train HMM classifiers in [16] and reported high classification rates.
Further results confirm that, although the number of acquired samples is dramatically reduced, we can still obtain high classification rates.
From all existing classification schemes, a SVM-based technique has been selected due to high classification rates obtained in previous works [33] and to their high generalization abilities.
This task was very small and it is unclear whether the high classification rates would be achievable for a larger-scale experiment.
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